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DaCy: An efficient and unified framework for danish NLP

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DaCy is a Danish natural language preprocessing framework made with SpaCy. Its largest pipelines has achieved State-of-the-Art performance on Named entity recognition, part-of-speech tagging, dependency parsing and Danish, but it also integrates pipelines for emotion detection, sentiment analysis, coreference resolution and more.

🔧 Installation

You can install dacy via pip from PyPI:

pip install dacy

👩‍💻 Usage

To use the model you first have to download either the small, medium, or large model. To see a list of all available models:

import dacy
for model in dacy.models():
    print(model)
# ...
# da_dacy_small_trf-0.2.0
# da_dacy_medium_trf-0.2.0
# da_dacy_large_trf-0.2.0

To download and load a model simply execute:

nlp = dacy.load("da_dacy_medium_trf-0.2.0")
# or equivalently (always loads the latest version)
nlp = dacy.load("medium")

To see more examples, see the documentation.

📖 Documentation

Documentation
📚 Getting started Guides and instructions on how to use DaCy and its features.
🦾 Performance A detailed description of the performance of DaCy and comparison with similar Danish models
📰 News and changelog New additions, changes and version history.
🎛 API References The detailed reference for DaCy's API. Including function documentation
🙋 FAQ Frequently asked questions

Training and reproduction

The folder training contains a range of folders with a SpaCy project for each model version. This allows for the reproduction of the results.

Want to learn more about how DaCy initially came to be, check out this blog post.


💬 Where to ask questions

To report issues or request features, please use the GitHub Issue Tracker. Questions related to SpaCy are kindly referred to the SpaCy GitHub or forum. Otherwise, please use the Discussion Forums.

Type
📚 FAQ FAQ
🚨 Bug Reports GitHub Issue Tracker
🎁 Feature Requests & Ideas GitHub Issue Tracker
👩‍💻 Usage Questions GitHub Discussions
🗯 General Discussion GitHub Discussions

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